8h %SSKrSSKrSSKJr SSKJr SSKJrJrJ r J r SSK r SSK J r SSKJr SSKJrJrJr /SQr\ R*R,\ R*R.R01\ R*R2\ R*R.R41\ R*R6\ R*R.R81\ R*R:\ R*R.R<\ R*R.R>1\ R*R@\ R*R.RB1\ R*RD\ R*R.RF\ R*R.RH1\ RJ\RJ\RLS S 1\ RN\RN\RPS S 1/q)\*\+\,S 'Sr-\-"5q.S\*\+4Sjr/S"Sjr0S\\4Sjr1Sr2S\*\4Sjr3S#S\ RhRjS\*\S\ \\/\644Sjjr7S\ RhRjS\ RhRS\8S\9\:\ R*Rv\ RhR44Sjrg)$N) OrderedDict)Sequence)AnyCallableOptionalUnion)ExportedProgram)Node)check_subgraphs_connectedget_source_partitionsSourcePartition)find_sequential_partitionsget_equivalent_typesupdate_equivalent_types_dictbfs_trace_with_node_processaddadd_mulmul__EQUIVALENT_TYPEScP0n[HnUHn[U5X'M M U$N)rlist)_DICTvaluesvs `/var/www/fran/franai/venv/lib/python3.13/site-packages/torch/ao/quantization/pt2e/graph_utils.py_create_equivalent_types_dictr%s- E#AF|EH$ Lreturnc[$r)rrrrr0s rc8Uc [S5eUq[5qg)zHelp function for user who wants to customize the _EQUIVALENT_TYPES and _EQUIVALENT_TYPES_DICT. When customized_equivalent_types passes in, re-generate _EQUIVALENT_TYPES and _EQUIVALENT_TYPES_DICT. Nz.customized_equivalent_types should not be None) ValueErrorrr_EQUIVALENT_TYPES_DICT)customized_equivalent_typess rrr4s' #*IJJ4:<r partitionscHSnUHnUb[X5(d gUnM g)NFT)r )r'prev_partition partitions r_partitions_sequentialr+As6N  %.G / / "  rcPU/nU[;aUR[U5 U$r)r%extend)partition_typematching_typess r_get_matching_typesr0Ls-$%N//4^DE rpartition_typesc[5nUH0n[U5n[U5n[X-5S:a gX-nM2 g)NrFT)setr0len)r1partition_types_setr.r/matching_types_sets r_valid_type_sequencer7SsK%),^< 0 "7 81 <1 * rgm filter_fnc[U5(d[SUS35e[5nUH\n[U5n[ UR Xc5n[ [RRUR555XE'M^ [ UR55n[R"U6n U V s/sHn [U 5(dMU PM n n U $s sn f)NzInvalid partition types: z*. Each type in the sequence must be unique) r7r$rr0r graphr itertoolschain from_iterablerproductr+) r8r1include_functional_equivalentr9typed_partitionsr.types_to_matchr'typed_partitions_listfusion_candidates candidatefused_partitionss rrr^s  0 0''88b c  AL ),^<*288^O +/ OO ) )**;*;*= >, (*!!1!8!8!:;!))+@A+*I !) , *  s <CC graph_modulenode arg_indexc.URUn[U[RR5(deUR S:Xde[UR [5(deURUR 5nUR XA4$)Nget_attr) args isinstancetorchfxr optargetstr get_submodule)rGrHrI submod_node submodules r_get_submodulerV{s))I&K k588== 1 11 1 >>Z '' ' k((# . .. .**;+=+=>I   y ..rc/nURRHnURS:waMUR[R R RLa6UR[XS55 UR[XS55 UR[R R RLdMUR[XS55 M U$)ac Returns a list of submodules used for control flow operations (torch.ops.higher_order.cond/map) that are in the given toplevel graph (does not look into submodules). Specifically, the returned value is a list containing a tuple of (name of the submodule that's stored in the graph module, the submodule itself, and the fx node that uses this submodule). call_functionr) r;nodesrPrQrNops higher_ordercondappendrVmap_impl)rGcontrol_flow_submodulesrHs r_get_control_flow_submodulesrbs!""(( 77o %  ;;%))0055 5 # * *>,a+P Q # * *>,a+P Q ;;%))0099 9 # * *>,a+P Q) #"rmodelnode_opc[U[[RR45(dS[ U535e[U[5(a UR OUnU/nU(aURS5nURRHnURS;aMU"U5 M [U5VVs/sHupgnUPM nnnURU5 U(aMggs snnf)z9Traverse the graph module and apply node_op to each node.z-Expected GraphModule or ExportedProgram, got r)output placeholderN) rMr rNrO GraphModuletyperGpopr;r[rPrbr-) rcrdr8queuecurrent_graph_modulerH_rUras rrrs eouxx/C/CD E E 7U }E E *%AA  uB DE $yy|(..44Dww33 DM 5$@@T#U# #Ua #U #   ,- %# sC4r)TN)?r<operator collectionsrcollections.abcrtypingrrrrrN torch.exportr torch.fxr *torch.fx.passes.utils.source_matcher_utilsr r r __all__nnConv1d functionalconv1dConv2dconv2dAdaptiveAvgPool2dadaptive_avg_pool2dReLUrelurelu_ BatchNorm2d batch_normHardtanhhardtanh hardtanh_riaddrimulrrr3__annotations__rr%rrr+r0r7rOrhboolrinttuplerRModulerVrbrr"rrrs#$11 (  XX__ehh))001 XX__ehh))001 XX!4!4!H!HI XX]]EHH'',,ehh.A.A.G.GH XX588..99: XX++44ehh6I6I6S6ST YY hmmUF; YY hmmUF; 49 78d3i =x'@$s)#'26  #Y$./ : /((&& /.3hhmm /HK / 3 ./ /#((&&# %UXX__ehhmm3 45#0. %(("6"66 7.BJ. .r